Cited by 174

The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.

AI Chatbots in Digital Mental Health

Balcombe, Luke·2023·Informatics

Abstract

Artificial intelligence (AI) chatbots have gained prominence since 2022. Powered by big data, natural language processing (NLP) and machine learning (ML) algorithms, they offer the potential to expand capabilities, improve productivity and provide guidance and support in various domains. Human–Artificial Intelligence (HAI) is proposed to help with the integration of human values, empathy and ethical considerations into AI in order to address the limitations of AI chatbots and enhance their effectiveness. Mental health is a critical global concern, with a substantial impact on individuals, communities and economies. Digital mental health solutions, leveraging AI and ML, have emerged to address the challenges of access, stigma and cost in mental health care. Despite their potential, ethical and legal implications surrounding these technologies remain uncertain. This narrative literature review explores the potential of AI chatbots to revolutionize digital mental health while emphasizing the need for ethical, responsible and trustworthy AI algorithms. The review is guided by three key research questions: the impact of AI chatbots on technology integration, the balance between benefits and harms, and the mitigation of bias and prejudice in AI applications. Methodologically, the review involves extensive database and search engine searches, utilizing keywords related to AI chatbots and digital mental health. Peer-reviewed journal articles and media sources were purposively selected to address the research questions, resulting in a comprehensive analysis of the current state of knowledge on this evolving topic. In conclusion, AI chatbots hold promise in transforming digital mental health but must navigate complex ethical and practical challenges. The integration of HAI principles, responsible regulation and scoping reviews are crucial to maximizing their benefits while minimizing potential risks. Collaborative approaches and modern educational solutions may enhance responsible use and mitigate biases in AI applications, ensuring a more inclusive and effective digital mental health landscape.

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Crossref · 10.3390/informatics10040082

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  • Systematic reviews broadly support the potential of CBT-inspired chatbots to assist individuals with mild-to-moderate mental health conditions, though they call for more rigorous long-term evaluation and clearer clinical governance frameworks.

    “Systematic reviews broadly support the potential of CBT-inspired chatbots to assist individuals with mild-to-moderate mental health conditions, though they also call for more rigorous long-term evaluation and clearer clinical governance frameworks (Balcombe, 2023;Casu et al., 2024;Gallegos et al., 2024;Kwon et al., 2024).”

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Research works printed but not linked: 36

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Metadata

Authors
Balcombe, L.
Venue
Informatics
Publisher
MDPI AG
Published
2023-10-27
Volume
10
Issue
4
Pages
82
ISSN
2227-9709
Cited by
174
References
29
Language
en

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